Abstract

With the current growth of data centers, improving energy saving is becoming more important to cloud service providers. The data centers architectural design and the advancement of virtualization technologies can be exploited for energy saving. In this paper, we studied the energy saving problem in data centers using virtual machines placement and live migration taking to account the status of the network links load. The problem was formulated as multi-objective integer linear program, which solvable by CPLEX, to minimize the energy consumed by the servers and minimize the time to migrate virtual machines. To overcome CPLEX high computation, a heuristic algorithm is introduced to provide practical and efficient virtual machines placement while minimizing their migration overhead to the network. The heuristic is evaluated in terms of energy consumed and performance using a real data center testbed that is stressed by running Hadoop Hibench benchmarks. The results where compared to the ones obtained by distributed resource scheduler (DRS) and the base case. The results show that the heuristic algorithm can save up to 30% of the server’s energy. For scalability and validity of optimality, the results of the heuristic were compared to the ones provided by CPLEX where the gap difference was less than 7%.